Intelligent Reflecting Surfaces: Sum-Rate Optimization Based on Statistical CSI

In this paper, we consider a multi-user multiple-input multiple-output (MIMO) system aided by multiple intelligent reflecting surfaces (IRSs) that are deployed to increase the coverage and, possibly, the rank of the channel. We propose an optimization algorithm to configure the IRSs, which is aimed at maximizing the network sum-rate by exploiting only the statistical characterization of the environment, such as the distribution of the locations of the users and the distribution of the multipath channels. As a consequence, the proposed approach does not require the estimation of the instantaneous channel state information (CSI) for system optimization, thus significantly relaxing (or even avoiding) the need of frequently reconfiguring the IRSs, which constitutes one of the most critical issues in IRS-assisted systems. Numerical results confirm the validity of the proposed approach. It is shown, in particular, that IRS-assisted wireless systems that are optimized based on statistical CSI still provide large performance gains as compared to the baseline scenarios in which no IRSs are deployed.Comment: submitted for journal publicatio

System-Level Modelling and Beamforming Design for RIS-assisted Cellular Systems

Reconfigurable intelligent surface (RIS) is considered as key technology for improving the coverage and network capacity of the next-generation cellular systems. By changing the phase shifters at RIS, the effective channel between the base station and user can be reconfigured to enhance the network capacity and coverage. However, the selection of phase shifters at RIS has a significant impact on the achievable gains. In this letter, we propose a beamforming design for the RIS-assisted cellular systems. We then present in detail the system-level modelling and formulate a 3-dimension channel model between the base station, RIS, and user, to carry out system-level evaluations. We evaluate the proposed beamforming design in the presence of ideal and discrete phase shifters at RIS and show that the proposed design achieves significant improvements as compared to the state-of-the-art algorithms

Memory-Enhanced Dynamic Evolutionary Control of Reconfigurable Intelligent Surfaces

An innovative evolutionary method for the dynamic control of reconfigurable intelligent surfaces (RISs) is proposed. It leverages, on the one hand, on the exploration capabilities of evolutionary strategies and their effectiveness in dealing with large-scale discrete optimization problems and, on the other hand, on the implementation of memory-enhanced search mechanisms to exploit the time/space correlation of communication environments. Without modifying the base station (BS) beamforming strategy and using an accurate description of the meta-atom response to faithfully account for the micro-scale EM interactions, the RIS control (RISC) algorithm maximizes the worst-case throughput across all users without requiring that the Green's partial matrices, from the BS to the RIS and from the RIS to the users, be (separately) known/measured. Representative numerical examples are reported to illustrate the features and to assess the potentialities of the proposed approach for the RISC

Intelligent Omni-Surfaces for Full-Dimensional Wireless Communications: Principle, Technology, and Implementation

The recent development of metasurfaces has motivated their potential use for improving the performance of wireless communication networks by manipulating the propagation environment through nearly-passive sub-wavelength scattering elements arranged on a surface. However, most studies of this technology focus on reflective metasurfaces, i.e., the surface reflects the incident signals towards receivers located on the same side of the transmitter, which restricts the coverage to one side of the surface. In this article, we introduce the concept of intelligent omni-surface (IOS), which is able to serve mobile users on both sides of the surface to achieve full-dimensional communications by jointly engineering its reflective and refractive properties. The working principle of the IOS is introduced and a novel hybrid beamforming scheme is proposed for IOS-based wireless communications. Moreover, we present a prototype of IOS-based wireless communications and report experimental results. Furthermore, potential applications of the IOS to wireless communications together with relevant research challenges are discussed